* feat: Add DeepSeek thinking mode support for OpenAI compatibility layer
- Add DeepSeek reasoning models support (deepseek-reasoner and DeepSeek-V3.2)
- Automatic thinking mode detection based on model name
- Inject thinking parameters in request body (both official API and vLLM formats)
- Preserve reasoning_content in message conversion for tool call iterations
- Extract buildOpenAIRequestBody() for testability
- Treat multimodal inputs (e.g. images) as new turn boundaries
- Fix env var cleanup in tests to prevent state leak
Signed-off-by: guunergooner <tongchao0923@gmail.com>
* docs: update contributors
---------
Signed-off-by: guunergooner <tongchao0923@gmail.com>
Co-authored-by: guunergooner <18660867+guunergooner@users.noreply.github.com>
Fixes#168
OpenAI requires that an assistant message with tool_calls be immediately
followed by tool messages. Previously, convertInternalUserMessage
output user content before tool results, causing 400 errors.
Now tool messages are pushed first.
Two fixes for OpenAI-compatible provider compatibility:
1. Sanitize JSON Schema `const` → `enum` in tool parameters.
Many OpenAI-compatible endpoints (Ollama, DeepSeek, vLLM, etc.)
do not support the `const` keyword in JSON Schema. Recursively
convert `const: value` to `enum: [value]` which is semantically
equivalent.
2. Force stop_reason to `tool_use` when tool_calls are present.
Some backends incorrectly return finish_reason "stop" even when
the response contains tool_calls. Without this fix, the query
loop treats the response as a normal end_turn and never executes
the requested tools.
